402 research outputs found
Polish army soldier and scientist – Stanisław Ossowski
No full textArtykuł przypomina Stanisława Ossowskiego, wybitnego socjologa i politologa, reprezentanta Szkoły Lwowsko-Warszawskiej i żołnierza. Autorka koncentruje uwagę na dwóch wybranych z jego twórczości problemach: na człowieku jako podmiocie etycznym oraz na szansach i zagrożeniach, które wspomagają albo które zakłócają przebieg procesów kształtowania jednostkowych i zbiorowych osobowości społecznych. Stanisław Ossowski za zawodowy obowiązek uczonego, zwłaszcza humanisty badającego systemy idei i systemy wartości, uważał nieposłuszeństwo w myśleniu, wiernośc prawdzie i intelektualną uczciwość. Uzasadniał teorię o wzajemnym warunkowaniu się struktury społecznej i kultury oraz o wzajemnym uzależnianiu od struktury społecznej – osobowości. Badał wpływ decyzji urzędników rządowych wyższego szczebla na dynamikę ludzkich zachowań i na kształtowanie się ludzkiego polimorfizmu.The article reminds Stanisław Ossowski, an outstanding sociologist and political scientist, a representative of the Lviv-Warsaw school, and a brave soldier. The author focuses her attention on two problems selected from his work: on man as an ethical subject and on opportunities and threats in shaping individual and collective social personalities. Stanisław Ossowski regarded disobedience in thinking, faithfulness to the truth, and intellectual honesty as the professional duty of a scientist, especially a humanist, who studies ideas and value systems. He justified the theory of mutual conditioning of the social structure-personality. He studied the impact of decisions of senior government officials on the dynamics of human behaviour and the development of human polymorphism
On the evolution of cancer genomes : Signatures of selection reveal cancer genes across multiple tumor types
No full textTumors are composed of fast-growing cells that become malignant under selection of biological functions needed for cancer development. In this thesis, I intend to uncover the basic evolutionary principles underlying cancer etiology. The first part constitutes a longitudinal analysis of a single CLL case, which tumor heterogeneity and clonal evolution were revealed by sequencing. The second explores the signatures of positive selection of somatic mutations allowing the identification of driver genes. The last part is an attempt to uncover the essential functions of the cancer cell using signals of purifying selection. Altogether, we have identified a landscape of cancer-related genes that can be used for improving current cancer treatments.El tumor esta compuesto de células que crecen indiscriminadamente, bajo la lupa de selección natural. En esta tesis hemos intentado reconstruir los principios básicos de la evolución del cáncer, como estos describen la adquisición de mutaciones que inician la malignidad tumoral. El primer trabajo es un anaálisis genómico de un paciente con leucemia. El Segundo explora la heterogeneidad intratumoral para identificar genes drivers del cáncer. Y el último trabajo se enfoca en desenmascarar las señales de selección negativa. Nuestros resultados de estos tres trabajos constituyen una fuente de nuevos genes que pueden ser explorados como dianas terapéuticas del cáncer.Programa de doctorat en Biomedicin
Computational analysis of epigenomic variability and its effect on regulatory activity
No full textEpigenetics provides a plausible link between the environment and changes in gene expression that might contribute to disease phenotypes. The main goal of the thesis is to study epigenomic variability and their effect on the regulatory activity underlying chromatin dynamics. With an ultimate aim to identify regulatory variants driving cancer as well as disease specific epigenomic patterns in neurological diseases, the thesis deals with the development and subsequent implementation of a novel supervised machine-learning based enhancer predictor (GEP). Further, to address the role of DNA methylation during development of two distinct larval morphs from a single egg in a parasitic polyembryonic wasp, we have developed a novel computational method (dMeth-X) that identifies putative differentially methylated genes responsible for morphological and behavioral differences between the larval forms. Additionally, the thesis focuses on the study of the effect of external factors on the epigenomic variability on the mouse brain cortex. Overall, we believe that my doctoral thesis is a successful endeavor to study the epigenetic variability and regulatory activity using next-generation sequencing approaches.La epigenética proporciona un enlace plausible entre el medio ambiente y los cambios en la expresión de genes que podrían contribuir a fenotipo de las enfermedades. El objetivo principal de la tesis es el estudio de la variabilidad epigenómica y su efecto sobre la actividad reguladora subyacente a la dinámica de la cromatina. Con un objetivo último de identificar variantes de regulación que contribuyen al cáncer, así como patrones epigenómicos específicos en enfermedades neurológicas, las tesis se enfoca en el desarrollo y posterior aplicación de un nuevo método supervisado para predecir potenciadores basado en aprendizaje automático (GEP). Además, para abordar el papel de la metilación del ADN en la configuración de dos formas larvarias distintas de un solo huevo en una avispa poliembriónica parasitaria, hemos desarrollado un nuevo método computacional (dMeth-X) para identificar los genes diferencialmente metilados que podrían contribuir distinguiendo formas larvarias contrastantes. Adicionalmente, la tesis incorporó el estudio del efecto de factores externos sobre la variabilidad epigenómica de la corteza del cerebro de ratón. En general, creemos que mi tesis doctoral es un esfuerzo exitoso para estudiar la variabilidad epigenética y la actividad reguladora utilizando enfoques de secuenciación de próxima generación.Programa de doctorat en Biomedicin
On the evolution of cancer genomes : Signatures of selection reveal cancer genes across multiple tumor types
No full textTumors are composed of fast-growing cells that become malignant under selection of biological functions needed for cancer development. In this thesis, I intend to uncover the basic evolutionary principles underlying cancer etiology. The first part constitutes a longitudinal analysis of a single CLL case, which tumor heterogeneity and clonal evolution were revealed by sequencing. The second explores the signatures of positive selection of somatic mutations allowing the identification of driver genes. The last part is an attempt to uncover the essential functions of the cancer cell using signals of purifying selection. Altogether, we have identified a landscape of cancer-related genes that can be used for improving current cancer treatments.El tumor esta compuesto de células que crecen indiscriminadamente, bajo la lupa de selección natural. En esta tesis hemos intentado reconstruir los principios básicos de la evolución del cáncer, como estos describen la adquisición de mutaciones que inician la malignidad tumoral. El primer trabajo es un anaálisis genómico de un paciente con leucemia. El Segundo explora la heterogeneidad intratumoral para identificar genes drivers del cáncer. Y el último trabajo se enfoca en desenmascarar las señales de selección negativa. Nuestros resultados de estos tres trabajos constituyen una fuente de nuevos genes que pueden ser explorados como dianas terapéuticas del cáncer.Programa de doctorat en Biomedicin
Highly accurate variant detection for identification of tumor mutations and mosaic variants
No full textThe rapid development of high-throughput sequencing technologies pushed forward the fields of medical genomics and precision medicine, creating many new applications for diagnostics and clinical studies that require high quality data and highly accurate analysis methods. Distinguishing errors from real variants in Next Generation Sequencing data is a challenge when systematic errors, random sequencing errors, germline variants or somatic variants at very low allele frequency are present in the same data. In the first part of this thesis, we developed a genotype callability filter (ABB) able to identify systematic variant calling errors that were not found by state-of-the art methods. This tool cleans false positive calls from somatic and germline variant callsets, as well as detects false gene-disease associations in case-control studies. Secondly, we developed a set of novel methods able to distinguish and correct sequencing and PCR errors with the use of molecular barcodes, permitting us to build error rate models for the detection of somatic mutations at extremely low allele frequencies in liquid biopsies. As final part of this thesis, we characterized mosaic mutations in a multi-tissue, multi-individual study using a cohort of thousands of samples from hundreds of healthy individuals.El ràpid desenvolupament de les tecnologies de seqüenciació d’alt rendiment ha impulsat els camps de la genòmica mèdica i la medicina d’alta precisió, creant una gran varietat de noves aplicacions, les quals requereixen dades d’una qualitat excel·lent i mètodes d’anàlisi altament precisos. La distinció entre errors i variants reals en dades de seqüenciació de propera generació (NGS) és un repte quan hi ha errors sistemàtics o aleatoris mesclats amb variants germinals o somàtiques a freqüències al·lèliques molt baixes. En la primera part d'aquesta tesi, hem desenvolupat un filtre per al genotipatge de variants (ABB) capaç d'identificar errors sistemàtics durant el procés de detecció de variants que altres mètodes convencionals no poden trobar. Aquesta eina filtra falsos positius del conjunt de variants finals en estudis de variacions somàtiques i germinals, així com també detecta falses associacions de malalties gèniques en estudis de casos-controls. En segon lloc, hem desenvolupat un conjunt de nous mètodes capaços de distingir i corregir els errors de seqüenciació i PCR amb l’ús d’identificadors moleculars. Aquests ens permeten modelar les taxes d’error i conseqüentment detectar mutacions somàtiques a freqüències al·lèliques extremadament baixes en l’anàlisi de biòpsies líquides. Per finalitzar aquesta tesi, hem caracteritzat les mutacions mosaiques en un estudi multi-teixit multi-individu utilitzant una cohort de centenars d'individus sans amb milers de mostres.Programa de doctorat en Biomedicin
Computational Approaches for Next Generation Sequencing Analysis and MiRNA Target Search.
No full textComplementation contributes to transcriptome complexity in maize (Zea mays L.) hybrids relative to their inbred parents
No full textTypically, F1-hybrids are more vigorous than their homozygous, genetically distinct parents, a phenomenon known as heterosis. In the present study, the transcriptomes of the reciprocal maize (Zea mays L.) hybrids B73×Mo17 and Mo17×B73 and their parental inbred lines B73 and Mo17 were surveyed in primary roots, early in the developmental manifestation of heterotic root traits. The application of statistical methods and a suitable experimental design established that 34,233 (i.e., 86%) of all high-confidence maize genes were expressed in at least one genotype. Nearly 70% of all expressed genes were differentially expressed between the two parents and 42%–55% of expressed genes were differentially expressed between one of the parents and one of the hybrids. In both hybrids, ∼10% of expressed genes exhibited nonadditive gene expression. Consistent with the dominance model (i.e., complementation) for heterosis, 1124 genes that were expressed in the hybrids were expressed in only one of the two parents. For 65 genes, it could be shown that this was a consequence of complementation of genomic presence/absence variation. For dozens of other genes, alleles from the inactive inbred were activated in the hybrid, presumably via interactions with regulatory factors from the active inbred. As a consequence of these types of complementation, both hybrids expressed more genes than did either parental inbred. Finally, in hybrids, ∼14% of expressed genes exhibited allele-specific expression (ASE) levels that differed significantly from the parental-inbred expression ratios, providing further evidence for interactions of regulatory factors from one parental genome with target genes from the other parental genome.This article is published as Paschold, Anja, Yi Jia, Caroline Marcon, Steve Lund, Nick B. Larson, Cheng-Ting Yeh, Stephan Ossowski et al. "Complementation contributes to transcriptome complexity in maize (Zea mays L.) hybrids relative to their inbred parents." Genome research 22, no. 12 (2012): 2445-2454. doi: 10.1101/gr.138461.112.</p
On principles organizing social order. An attempt to reinterpret the typology of collective behaviours by St. Ossowski
No full textThe starting point of this article is the typology of collective behaviours by
St. Ossowski. The purpose of the considerations is an attempt to formulate
a general form of each of the three basic types and to present research possibilities
offered by this theoretical conception.
The author assumes that the most fundamental element differentiating between
particular types of order are the principles organizing social order. Three basic
principles can be distinguished: 1) rationality — prevailing in organizing the
behaviours of the policentric type; 2) functionality — prevailing in monocentric
collectivities; and 3) traditionality — prevailing in collectivities characterized by
the internal order of the „collective representations" type.
Besides, within each of the principles one can distinguish various criteria
whose maximalisation the principle is to serve. The classification of a given
collectivity into one of the basic types of collective behaviours makes it necessary
to indicate these two categories; other differences may be treated as reducible
to the above two categories.Digitalizacja i deponowanie archiwalnych zeszytów RPEiS sfinansowane przez MNiSW w ramach realizacji umowy nr 541/P-DUN/201
Jan Paweł II a demokracja
No full textThe Author observes a certain paradox: on the one hand John Paul II sharply criticized modern liberal democracy, but on the other such words were uttered by the man who took credit for an immense, if not decisive, contribution to the collapse of Communism and the birth of democracy in Central and Eastern Europe. This contradiction, however, is only apparent since John Paul II, and the Catholic Church, perceived and defined democracy in a particular way. Their way is in many aspects contradictory to the principles of a modern model of democracy, that is liberal democracy, prevailing in Europe and elsewhere.The Author observes a certain paradox: on the one hand John Paul II sharply criticized modern liberal democracy, but on the other such words were uttered by the man who took credit for an immense, if not decisive, contribution to the collapse of Communism and the birth of democracy in Central and Eastern Europe. This contradiction, however, is only apparent since John Paul II, and the Catholic Church, perceived and defined democracy in a particular way. Their way is in many aspects contradictory to the principles of a modern model of democracy, that is liberal democracy, prevailing in Europe and elsewhere
AI Model for Predicting Anti-PD1 Response in Melanoma Using Multi-Omics Biomarkers
No full textBackground: Immune checkpoint inhibitors (ICIs) have demonstrated significantly improved clinical efficacy in a minority of patients with advanced melanoma, whereas non-responders potentially suffer from severe side effects and delays in other treatment options. Predicting the response to anti-PD1 treatment in melanoma remains a challenge because the current FDA-approved gold standard, the nonsynonymous tumor mutation burden (nsTMB), offers limited accuracy. Methods: In this study, we developed a multi-omics-based machine learning model that integrates genomic and transcriptomic biomarkers to predict the response to anti-PD1 treatment in patients with advanced melanoma. We employed least absolute shrinkage and selection operator (LASSO) regression with 49 biomarkers extracted from tumor–normal whole-exome and RNA sequencing as input features. The performance of the multi-omics AI model was thoroughly compared to that of nsTMB alone and to models that use only genomic or transcriptomic biomarkers. Results: We used publicly available DNA and RNA-seq datasets of melanoma patients for the training and validation of our model, forming a meta-cohort of 449 patients for which the outcome was recorded as a RECIST score. The model substantially improved the prediction of anti-PD1 outcomes compared to nsTMB alone, with an ROC AUC of 0.7 in the training set and an ROC AUC of 0.64 in the test set. Using SHAP values, we demonstrated the explainability of the model’s predictions on a per-sample basis. Conclusions: We demonstrated that models using only RNA-seq or multi-omics biomarkers outperformed nsTMB in predicting the response of melanoma patients to ICI. Furthermore, our machine learning approach improves clinical usability by providing explanations of its predictions on a per-patient basis. Our findings underscore the utility of multi-omics data for selecting patients for treatment with anti-PD1 drugs. However, to train clinical-grade AI models for routine applications, prospective studies collecting larger melanoma cohorts with consistent application of exome and RNA sequencing are required
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